Q: What do you get when you combine deep financial management expertise and AI-powered Extended Planning and Analysis with IBM’s new technology accelerator?
A: A Minimum Viable Product (MVP) using IBM Planning Analytics with Watson designed, built and deployed in 3 weeks by IBM Partner, Chartertech, and IBM Client Engineering.
Below you’ll find a short story about what happens when two teams combine to fast-track an enterprise-level project. How, through co-creation, financial advisory software and technology specialists Chartertech and IBM brought the necessary diligence, passion, and skills to deliver a scalable, end-to-end product in a narrowing timeframe.
Three weeks and counting.
It’s Friday afternoon, and IBM Client Engineering receives a phone call to help deliver a new business application that:
- Empowers clients to provide quantifiable answers when faced with critical operational questions.
- Standardises enterprise data visualisation in a single, highly customisable User Experience (UX).
- Helps Leadership make data-driven decisions with the appropriate level of justification.
The first truth to delivering a rapid prototype is to get started on iteration zero before you have time to dwell. Iteration ‘zero’ because it alleviates the pressure of what will be the first version you release. It allows for learning during the early design and development phases, a mindset essential to succeed in sprint-based innovation projects.
The second truth is that you can’t do it alone. The benefits of a diverse team co-creating far outweigh the drawbacks of a new team — see Bruce Tuckman’s Forming, Storming, Norming and Performing as described here by Judith Stein. To this extent, the squad of IBM technical talent gear up to work — at pace — alongside Chartertech SMEs on the finance technology solution. Our hack to overcome working together for the first time is to embrace Enterprise Design Thinking.
To put out incredible benefits to the user, we need to understand them. With little end-user access, we opted to create personas using accurate, referenceable data. We ran workshops in Mural that tested our hypothesis, validated the information architecture, and mapped the product flow against user needs. At the risk of sounding cliché, it is a case of going slow to move fast, resisting the urge to dive straight into developing the product. We could make strategic decisions that focus our MVP on the right deliverables by slowing down—minimising productivity waste whilst maximising agility—saving us time and money.
Two days into week one.
It’s time to prototype. In IBM Client Engineering, we call this step a Design Push — 5 days to rapidly design and prototype the vision with a ‘just-enough’ mindset. Moreover, you can still use this time effectively on the build side, working through setup and enablement, effectively reducing the development tasks. Which — spoiler — we did.
We achieved our North Star at the end of week one thanks to IBM’s open source Carbon Design System — now available in Figma — which allowed us to feed two birds with one scone:
- The Carbon components act as wireframing blocks that enable us to deliver high-fidelity screens and create a fantastic User Interface (UI) without hassle in a short timeframe.
- The fidelity aligns the team and empowers the developers to run full steam ahead, using Carbon’s theme and colour palette to configure inside Planning Analytics Workspace.
“This has been a fantastic interaction. The difference in quality between what we had two weeks ago and where we are now is outstanding! Thank you for your expertise, knowledge, and ability to deliver a result quickly.” John Vaughan, Associate Director, Chartertech
Our last two weeks.
Having worked hard on the platform in parallel to the UX, vast progress was made leveraging the capabilities of IBM Planning Analytics supported by IBM’s Cloud Pak for Data.
An important note is that IBM’s Planning Analytics with Watson does much more than just planning:
- It goes beyond automation to help you uncover new insights directly from your data.
- It enables users to forecast outcomes based on evolving trends or predictive insights and perform in-depth, what-if scenario analysis to test alternative assumptions through the power of AI.
- It can be deployed on-cloud, on-premise, on IBM Cloud Pak for Data, or as a hybrid option.
IBM Cloud Pak for Data is a platform with a scalable, robust and secure data fabric architecture, hosted on Red Hat OpenShift. It connects siloed data distributed across a hybrid cloud landscape, no matter where it resides. The outcome is highly user-friendly, and the non-technical interface allows the customisation of data sets usually reserved for the workbench of a data scientist.
With Red Hat OpenShift as the underlying platform, we streamlined the build using ARM templates, which enable authorised users to stand up resources using a simple, intuitive UI. It works quickly and efficiently, even with little technical knowledge. We created and deployed these templates by pairing up to work on programming tasks within a few days.
The secret sauce? Unapologetic collaboration. We leveraged Lean Startup ceremonies, Pair Programming and IBM Value Engineering Method that includes IBM Enterprise Design Thinking and Agile to ensure consistent participation and delivery of a validated result.
“I really like these stand-ups; they’re organised, fast and fruitful.” Heath Kinder, Lead Developer, Chartertech
IBM Client Engineering is an investment by IBM to jointly innovate and rapidly prove solutions to your business opportunities by leveraging IBM Technology. You bring your business and IT context, sponsorship, SMEs, and data. We carry a deeply skilled multi-disciplinary squad, industry knowledge, technical accelerators, and memorable experience.
Chartertech delivers tailored and scalable end-to-end business solutions in the space where finance meets technology. The team is from diverse backgrounds with proven experience working with government and private organisations.
Jeffrey Ginsburg is a Squad Leader and Design Lead in the A/NZ IBM Client Engineering team. The above article is personal and does not necessarily represent IBM’s positions, strategies, or opinions.